{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:N27DV3RP7WXW6BUAZU7G4BQE6I","short_pith_number":"pith:N27DV3RP","canonical_record":{"source":{"id":"1906.08879","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T22:08:51Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"c458d4307664e7abeb444b80ba0cf0cf4c1d1b16b6432c30ec59458b1a142c83","abstract_canon_sha256":"12bfe41fcac99d6911c2e2ba280f709919f6becb5fa4fa6651ec474b37009299"},"schema_version":"1.0"},"canonical_sha256":"6ebe3aee2ffdaf6f0680cd3e6e0604f21ef925cb2eeebb2a725b7ea01f928c78","source":{"kind":"arxiv","id":"1906.08879","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.08879","created_at":"2026-05-17T23:42:47Z"},{"alias_kind":"arxiv_version","alias_value":"1906.08879v1","created_at":"2026-05-17T23:42:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.08879","created_at":"2026-05-17T23:42:47Z"},{"alias_kind":"pith_short_12","alias_value":"N27DV3RP7WXW","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"N27DV3RP7WXW6BUA","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"N27DV3RP","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:N27DV3RP7WXW6BUAZU7G4BQE6I","target":"record","payload":{"canonical_record":{"source":{"id":"1906.08879","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T22:08:51Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"c458d4307664e7abeb444b80ba0cf0cf4c1d1b16b6432c30ec59458b1a142c83","abstract_canon_sha256":"12bfe41fcac99d6911c2e2ba280f709919f6becb5fa4fa6651ec474b37009299"},"schema_version":"1.0"},"canonical_sha256":"6ebe3aee2ffdaf6f0680cd3e6e0604f21ef925cb2eeebb2a725b7ea01f928c78","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:47.560346Z","signature_b64":"lmd95DoGK/nqs8/tYKnrYm8z4VAu0zY85hPN52H47k5KToTCgmXlk7+SLmKpUJOpWyA5JKcn7JvBx3XZesKjBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6ebe3aee2ffdaf6f0680cd3e6e0604f21ef925cb2eeebb2a725b7ea01f928c78","last_reissued_at":"2026-05-17T23:42:47.559784Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:47.559784Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.08879","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:42:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qUzYOpPHjJP5l/sxe+Ml4U/depCmRbuLOl5AeyyrazCfzHxwti8GOhahp9vx6QsgEsO2RzNZwcWzcwUcJBAdCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T08:14:31.856723Z"},"content_sha256":"73389e49591dcbe5a8e0989c7012f64bc78c86e12eb14fe2b86d35a06a4ebdf1","schema_version":"1.0","event_id":"sha256:73389e49591dcbe5a8e0989c7012f64bc78c86e12eb14fe2b86d35a06a4ebdf1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:N27DV3RP7WXW6BUAZU7G4BQE6I","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Hongzi Mao, Mohammad Alizadeh, Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta","submitted_at":"2019-06-20T22:08:51Z","abstract_excerpt":"We present Placeto, a reinforcement learning (RL) approach to efficiently find device placements for distributed neural network training. Unlike prior approaches that only find a device placement for a specific computation graph, Placeto can learn generalizable device placement policies that can be applied to any graph. We propose two key ideas in our approach: (1) we represent the policy as performing iterative placement improvements, rather than outputting a placement in one shot; (2) we use graph embeddings to capture relevant information about the structure of the computation graph, withou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.08879","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:42:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XO7T+j7MdBrmoQoMy/nCuVzKto5UaUjKLUjTziW/GKqO6cRm5MU9H7HMN/YvYV3EsKxLwIffUvWtbXBKGr0xDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T08:14:31.857384Z"},"content_sha256":"0732dd42b34c25b41d7ad5faebfd6566e8f35fde3db2eeb9e0755d17bcf95408","schema_version":"1.0","event_id":"sha256:0732dd42b34c25b41d7ad5faebfd6566e8f35fde3db2eeb9e0755d17bcf95408"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N27DV3RP7WXW6BUAZU7G4BQE6I/bundle.json","state_url":"https://pith.science/pith/N27DV3RP7WXW6BUAZU7G4BQE6I/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N27DV3RP7WXW6BUAZU7G4BQE6I/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-07T08:14:31Z","links":{"resolver":"https://pith.science/pith/N27DV3RP7WXW6BUAZU7G4BQE6I","bundle":"https://pith.science/pith/N27DV3RP7WXW6BUAZU7G4BQE6I/bundle.json","state":"https://pith.science/pith/N27DV3RP7WXW6BUAZU7G4BQE6I/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N27DV3RP7WXW6BUAZU7G4BQE6I/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:N27DV3RP7WXW6BUAZU7G4BQE6I","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"12bfe41fcac99d6911c2e2ba280f709919f6becb5fa4fa6651ec474b37009299","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T22:08:51Z","title_canon_sha256":"c458d4307664e7abeb444b80ba0cf0cf4c1d1b16b6432c30ec59458b1a142c83"},"schema_version":"1.0","source":{"id":"1906.08879","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.08879","created_at":"2026-05-17T23:42:47Z"},{"alias_kind":"arxiv_version","alias_value":"1906.08879v1","created_at":"2026-05-17T23:42:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.08879","created_at":"2026-05-17T23:42:47Z"},{"alias_kind":"pith_short_12","alias_value":"N27DV3RP7WXW","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"N27DV3RP7WXW6BUA","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"N27DV3RP","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:0732dd42b34c25b41d7ad5faebfd6566e8f35fde3db2eeb9e0755d17bcf95408","target":"graph","created_at":"2026-05-17T23:42:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We present Placeto, a reinforcement learning (RL) approach to efficiently find device placements for distributed neural network training. Unlike prior approaches that only find a device placement for a specific computation graph, Placeto can learn generalizable device placement policies that can be applied to any graph. We propose two key ideas in our approach: (1) we represent the policy as performing iterative placement improvements, rather than outputting a placement in one shot; (2) we use graph embeddings to capture relevant information about the structure of the computation graph, withou","authors_text":"Hongzi Mao, Mohammad Alizadeh, Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta","cross_cats":["cs.DC","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T22:08:51Z","title":"Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.08879","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:73389e49591dcbe5a8e0989c7012f64bc78c86e12eb14fe2b86d35a06a4ebdf1","target":"record","created_at":"2026-05-17T23:42:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"12bfe41fcac99d6911c2e2ba280f709919f6becb5fa4fa6651ec474b37009299","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T22:08:51Z","title_canon_sha256":"c458d4307664e7abeb444b80ba0cf0cf4c1d1b16b6432c30ec59458b1a142c83"},"schema_version":"1.0","source":{"id":"1906.08879","kind":"arxiv","version":1}},"canonical_sha256":"6ebe3aee2ffdaf6f0680cd3e6e0604f21ef925cb2eeebb2a725b7ea01f928c78","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6ebe3aee2ffdaf6f0680cd3e6e0604f21ef925cb2eeebb2a725b7ea01f928c78","first_computed_at":"2026-05-17T23:42:47.559784Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:47.559784Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lmd95DoGK/nqs8/tYKnrYm8z4VAu0zY85hPN52H47k5KToTCgmXlk7+SLmKpUJOpWyA5JKcn7JvBx3XZesKjBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:47.560346Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.08879","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73389e49591dcbe5a8e0989c7012f64bc78c86e12eb14fe2b86d35a06a4ebdf1","sha256:0732dd42b34c25b41d7ad5faebfd6566e8f35fde3db2eeb9e0755d17bcf95408"],"state_sha256":"95fcb518f4331133e5bbca4710377c8b97aab20ef88243cdc3740f67a4bec905"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Yk88wSkwt78GypKvOuN3kvKD8lBWif8NNbpqRVWvsCQFFiXUTveBbFB6cKCQeypotDKEDKJeqzT2DZ6KF2D3Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T08:14:31.860934Z","bundle_sha256":"c347c2cf3b555817c0e87a2e2aa7fd5c1703e956b2d59ab9cc3777977357419c"}}